Differential scanning fluorimetry (DSF) is an accessible, rapid, and economical biophysical technique that has seen many applications over the years, ranging from protein folding state detection to the identification of ligands that bind to the target protein. In this review, we discuss the theory, applications, and limitations of DSF, including the latest applications of DSF by ourselves and other researchers. We show that DSF is a powerful high-throughput tool in early drug discovery efforts. We place DSF in the context of other biophysical methods frequently used in drug discovery and highlight their benefits and downsides. We illustrate the uses of DSF in protein buffer optimization for stability, refolding, and crystallization purposes and provide several examples of each. We also show the use of DSF in a more downstream application, where it is used as an in vivo validation tool of ligand-target interaction in cell assays. Although DSF is a potent tool in buffer optimization and large chemical library screens when it comes to ligand-binding validation and optimization, orthogonal techniques are recommended as DSF is prone to false positives and negatives.
α-Ketoamide HCV protease inhibitors covalently bind to SARS-CoV-2 3CLpro. Boceprevir is a particular promising repurposed drug as it potently inhibits cellular viral proliferation.
The development of drug resistance by Mycobacterium tuberculosis and other pathogenic bacteria emphasizes the need for new antibiotics. Unlike animals, most bacteria synthesize isoprenoid precursors through the MEP pathway. 1-Deoxy-d-xylulose 5-phosphate synthase (DXPS) catalyzes the first reaction of the MEP pathway and is an attractive target for the development of new antibiotics. We report here the successful use of a loop truncation to crystallize and solve the first DXPS structures of a pathogen, namely M. tuberculosis (MtDXPS). The main difference found to other DXPS structures is in the active site where a highly coordinated water was found, showing a new mechanism for the enamine-intermediate stabilization. Unlike other DXPS structures, a “fork-like” motif could be identified in the enamine structure, using a different residue for the interaction with the cofactor, potentially leading to a decrease in the stability of the intermediate. In addition, electron density suggesting a phosphate group could be found close to the active site, provides new evidence for the D-GAP binding site. These results provide the opportunity to improve or develop new inhibitors specific for MtDXPS through structure-based drug design.
The goal of virtual screening is to generate a substantially reduced and enriched subset of compounds from a large virtual chemistry space. Critical in these efforts are methods to properly rank the binding affinity of compounds. Prospective evaluations of ranking strategies in the D3R grand challenges show that for targets with deep pockets the best correlations (Spearman ρ ~ 0.5) were obtained by our submissions that docked compounds to the holo-receptors with the most chemically similar ligand. On the other hand, for targets with open pockets using multiple receptor structures is not a good strategy. Instead, docking to a single optimal receptor led to the best correlations (Spearman ρ ~ 0.5), and overall performs better than any other method. Yet, choosing a suboptimal receptor for crossdocking can significantly undermine the affinity rankings. Our submissions that evaluated the free energy of congeneric compounds were also among the best in the community experiment. Error bars of around 1 kcal/mol are still too large to significantly improve the overall rankings. Collectively, our top of the line predictions show that automated virtual screening with rigid receptors perform better than flexible docking and other more complex methods.
The porcine epidemic diarrhea virus (PEDV) is an Alphacoronavirus (α-CoV) that causes high mortality in infected piglets, resulting in serious economic losses in the farming industry. Hypericin is a dianthrone compound that has been shown as an antiviral activity on several viruses. Here, we first evaluated the antiviral effect of hypericin in PEDV and found the viral replication and egression were significantly reduced with hypericin post-treatment. As hypericin has been shown in SARS-CoV-2 that it is bound to viral 3CLpro, we thus established a molecular docking between hypericin and PEDV 3CLpro using different software and found hypericin bound to 3CLpro through two pockets. These binding pockets were further verified by another docking between hypericin and PEDV 3CLpro pocket mutants, and the fluorescence resonance energy transfer (FRET) assay confirmed that hypericin inhibits the PEDV 3CLpro activity. Moreover, the alignments of α-CoV 3CLpro sequences or crystal structure revealed that the pockets mediating hypericin and PEDV 3CLpro binding were highly conserved, especially in transmissible gastroenteritis virus (TGEV). We then validated the anti-TGEV effect of hypericin through viral replication and egression. Overall, our results push forward that hypericin was for the first time shown to have an inhibitory effect on PEDV and TGEV by targeting 3CLpro, and it deserves further attention as not only a pan-anti-α-CoV compound but potentially also as a compound of other coronaviral infections.
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